Hidden Profile Control of Treatment and Correction: How an Unseen Record Can Decide How a Person Is Treated

This conceptual paper introduces Hidden Profile Control of Treatment and Correction, a mechanism in which a record or representation that a person cannot inspect directs how others treat them. The person experiences the consequences while lacking access to the account that organizes those responses. The paper assesses whether the representation is accurate, concerns the right person, remains current, and applies to the decision. The decision rule and treatment require separate justification. Shared reliance is not independent corroboration, and disclosure alone does not provide the ability to amend a record or circulate corrections. The discussion connects the mechanism to Solove’s work on databases and powerlessness and examines the appellate account in Ibrahim v. U.S. Department of Homeland Security (2019). The case concerns an erroneous watchlist designation, its consequences, and prolonged difficulty obtaining authoritative information and correcting related records despite early removal from the No Fly list. Part of the Interpretation and Feedback series within On Human Modeling, the paper asks who can inspect a profile, who can amend it, and who can carry a correction to those who used the earlier account. Its framework can inform human–AI research on how unseen profiles shape system responses and whether correction processes reach the records and systems that depend on them.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-10
DOI
https://doi.org/10.5281/zenodo.24119419
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Hidden Profile Control of Treatment and Correction: How an Unseen Record Can Decide How a Person Is Treated

Alexandra Cary
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Hidden Profile Control of Treatment and Correction: How an Unseen Record Can Decide How a Person Is Treated

Alexandra Cary
article en

Abstract

This conceptual paper introduces Hidden Profile Control of Treatment and Correction, a mechanism in which a record or representation that a person cannot inspect directs how others treat them. The person experiences the consequences while lacking access to the account that organizes those responses. The paper assesses whether the representation is accurate, concerns the right person, remains current, and applies to the decision. The decision rule and treatment require separate justification. Shared reliance is not independent corroboration, and disclosure alone does not provide the ability to amend a record or circulate corrections. The discussion connects the mechanism to Solove’s work on databases and powerlessness and examines the appellate account in Ibrahim v. U.S. Department of Homeland Security (2019). The case concerns an erroneous watchlist designation, its consequences, and prolonged difficulty obtaining authoritative information and correcting related records despite early removal from the No Fly list. Part of the Interpretation and Feedback series within On Human Modeling, the paper asks who can inspect a profile, who can amend it, and who can carry a correction to those who used the earlier account. Its framework can inform human–AI research on how unseen profiles shape system responses and whether correction processes reach the records and systems that depend on them.

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon